@misc{Ładyżyński_Piotr._Autor_Stock_2012, author={Ładyżyński, Piotr. Autor and Żbikowski, Kamil. Autor and Grzegorzewski, Przemysław Wojciech. Autor}, copyright={Creative Commons Attribution BY 4.0 license}, address={Warszawa}, journal={Raport Badawczy = Research Report}, howpublished={online}, year={2012}, publisher={Instytut Badań Systemowych. Polska Akademia Nauk}, publisher={Systems Research Institute. Polish Academy of Sciences}, language={eng}, abstract={The goal of this paper is to investigate if the strong ma­chine learning technique is able to retrieve information from past prices and predict price movements and future trends. The architecture of the system with the on-line adaptation ability to non-stationary two dimen­sional mixed Black-Scholes Markov time series model is presented. The methodology of investment strategies performance verification is also proposed.}, title={Stock Trading Random Forests, Trend Detection Tests and Force Index Volume Indicators}, type={Text}, keywords={Stock trading, Random forest, Trend detection test, Financial time serie, Quant fund, Investment strategies backtesting, Las losowy, Analiza trendu, Seria czasowa, Strategie inwestycyjne, Fundusze inwestycyjne, Handel akcjami}, }